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At least 1,621 records · Page 90

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NASA NTRSDate not supplied

Integral Velocity Sampling for Unsteady Rotor Models on Cartesian Meshes

An unsteady body-force rotor model utilizing integral velocity sampling is developed for Cartesian meshes with a focus on accurate performance predictions. In this approach, the rotors are modeled as body-force source terms, and integral sampling is used to define the local freestream velocity vector. The method is verified in two dimensions for airfoils, providing accurate angle of attack and freestream Mach number estimates even on relatively coarse meshes, and demonstrating excellent mesh convergence across a variety of source region thicknesses. Extensions of the model to three dimensions for both fixed and rotating wings are considered, with numerical experiments demonstrating the need for a spanwise-continuous representation of the induced velocity or angle of attack. The model provides reasonable spanwise lift distributions without any explicit tip-loss model. Comparisons to high-fidelity simulations and experimental data show excellent agreement for predictions of an isolated DJI Phantom 3 propeller in hover. Finally, simulations of the full aircraft in edgewise forward flight also compare well with wind tunnel data across a variety of pitch angles and propeller speeds.

ARMD↗

NASA NTRSDate not supplied

Scaling of Liquefaction Systems and the Effects of Gravity

Recent exploration initiatives both by NASA and others have produced interest in the liquefaction of fluids produced through in-situ processes on the surfaces of the Moon and Mars. Liquefaction of fluids in cryogenic temperatures is routinely done at large scale for terrestrial uses, but these processes do not necessarily scale down in an economical or technologically feasible manner for the anticipated rates of initial Lunar or Martian production plants. To understand appropriate processes and scaling parameters, various options should be considered. A multi-center team at NASA considered multiple different refrigeration cycles and refrigeration integration methodologies as well as how these might fit into early liquefaction plants. These studies resulted in the conclusion that integrating the tubing on the storage tank wall (for both structural and heat spreading reasons), preferably the tank which will actually use the fluid, is the nearest path forward. Given that assumption on the general framework of the liquefaction system, there are several different heat transfer mechanisms to consider from a scaling perspective. These include forced convection heat removal to the refrigeration system (or cryocooler), conduction through the tank wall heat exchanger, and condensation (with some natural convection) on the inner tank wall. Analysis of these mechanisms shows that while there is some sensitivity to gravitational level, that within the bounds of current interest (Lunar and Martian applications), this sensitivity does not dominate the liquefaction application. While there will be some effect, perhaps in a limiting manner as the tanks approach some high fill level, system level testing on the Earth should suffice for the performance prediction and demonstration of liquefaction operations as applicable to Lunar and Martian applications. However, as one approaches orbital conditions, this general approach to liquefaction will not be appropriate as the scaling of the heat transfer mechanisms is not appropriate. At this point, other approaches will need to be developed and demonstrated in the micro-gravity environment.

Cryogenics↗

NASA NTRSDate not supplied

Gravitational Effects on Liquefaction Systems for Lunar and Mars xploration

There is interest at NASA, other space agencies, and industry, in the liquefaction of fluids produced through in-situ processes on the surfaces of the Moon and Mars. A multi-center team at NASA recently considered multiple different refrigeration cycles and refrigeration integration methodologies and how these might fit into early liquefaction plants for NASA's exploration initiatives. The rate of liquefaction for these initiatives is quite slow in comparison to large scale terrestrial applications. These studies concluded that, for both structural and heat spreading reasons, integrating the refrigeration tubing on the surface of the storage tank wall is an attractive path to pursue in the near term. An analysis is performed of the condensation processes within the tank to determine the sensitivity of liquefaction to gravitational effects. The heat transfer mechanisms include forced convection heat removal to the refrigeration system (or cryocooler), conduction through the tank wall heat exchanger, and condensation on the inner tank wall. Gravity affects the liquefaction process via condensate liquid drainage, natural convection in the ullage, and the shape of the liquid-vapor interface in the tank. Analysis of these mechanisms shows that while there is some sensitivity to gravitational level in general, within the bounds of current interest (rate of liquefaction appropriate to Lunar and Martian applications), this sensitivity of liquefaction to gravity is quite small. Thus, system level testing on the Earth should suffice for the performance prediction and demonstration of liquefaction operations as applicable to lunar and Martian applications.

Cryogenics↗

NASA NTRSDate not supplied

Pretest Comprehensive Analysis for the Urban Air Mobility Side-by-Side Test Stand

The Urban Air Mobility (UAM) Side-by-Side Test Stand (SBS) is a two-rotor test stand designed and built at NASA Ames Research Center under the Revolutionary Vertical Lift Technology (RVLT) Project. The SBS entered service in the wind tunnel in the latter part of 2021 and allows for the experimental analysis of rotor-rotor interactions for UAM vehicles of the side-by-side variety. The SBS will allow investigation of the effect of numerous variables such as rotor lateral separation, rotor collective pitch, model pitch angle (𝛼), rotor rotation direction, and flight speed. This paper presents performance predictions for the SBS. These predictions, which were generated using CAMRAD II, provided increased assurance of the safe operational limits of the system. Additionally, these results, when compared with future data, will be used for validation of the computational models.

Comprehensive Analysis↗

NASA NTRS2020

Recent Developments in Tolerancing Methods for Imaging Spectrometers

We discuss detailed tolerancing methods developed for imaging spectrometers at NASA Jet Propulsion Laboratory, California Institute of Technology using the Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer as an illustrative example. We tolerance five metrics simultaneously: along-track response function, cross-track response function, spectral response function, spectral centroid uniformity, and spatial centroid uniformity. A method to calculate tolerancing sensitivities for each metric directly, a method to statistically combine Monte Carlo files from multiple tolerancing runs, and an example summary error budgets that communicate the key and driving tolerances for each metric are discussed. These methods facilitate rapid and semi-automated assessment of the predicted performance of imaging spectrometer systems from design through to assembly and launch life cycle, using metrics that are directly relevant to the extraction of accurate spectroscopic data from these instruments.

Mouroulis, Pantazis↗

NASA NTRS2020

Roman Space Telescope Coronagraph Engineering Design and Operating Concept

NASA’s Nancy Grace Roman Space Telescope (formerly known as WFIRST) is a flagship astrophysics mission planned for launch in 2025. The coronagraph instrument (CGI) on Roman will demonstrate the technology for direct imaging and spectroscopy of exoplanets around nearby stars. It will work with the obscured 2.4 meter diameter telescope and demonstrate starlight suppression that is up to 3 orders of magnitude deeper than the preceding space-based and ground-based coronagraphs by using active wavefront control in space with deformable mirrors. CGI has passed its Preliminary Design Review (PDR) in September 2019 and is working toward the instrument Critical Design Review (CDR) in the spring of 2021. We will describe the flow down of key and driving CGI requirements from high level performance to the instrument hardware and software, current instrument configuration and engineering design, operational concept planned for CGI observations, integrated modeling status, and performance predictions.

Tanga, Hong↗

NASA NTRS2022

Gravitational Effects on Liquefaction Systems for Lunar and Mars Exploration

There is interest at NASA, other space agencies, and industry, in the liquefaction of fluids produced through in-situ processes on the surfaces of the Moon and Mars. A multi-center team at NASA recently considered multiple different refrigeration cycles and refrigeration integration methodologies and how these might fit into early liquefaction plants for NASA's exploration initiatives. The rate of liquefaction for these initiatives is quite slow in comparison to large scale terrestrial applications. These studies concluded that, for both structural and heat spreading reasons, integrating the refrigeration tubing on the surface of the storage tank wall is an attractive path to pursue in the near term. In order to develop a technology development path and inform investors, it was desired to investigate the sensitivity of gravity of the processes involved. An analysis of the condensation processes within the tank is performed. The objective is to determine the sensitivity of liquefaction to gravitational effects. The heat transfer mechanisms include forced convection heat removal to the refrigeration system (or cryocooler), conduction through the tank wall heat exchanger, and convection and condensation on the inner tank wall. Gravity affects the liquefaction process via condensate liquid drainage, natural convection in the ullage, and the shape of the liquid-vapor interface within the tank. Analysis of these mechanisms shows that while there is some sensitivity to gravitational level in general, within the bounds of current interest (rate of liquefaction appropriate to Lunar and Martian applications, and cooling capacity of the cryocooler), this sensitivity of liquefaction to gravity is quite small. Thus, system level testing on the Earth should suffice for the performance prediction and demonstration of liquefaction operations as applicable to Lunar and Martian applications.

ISRU↗

NASA NTRS2021

Maximizing Dust Devil Follow-up Observations on Mars Using Cubesats and On-board Scheduling

Several million dust devil events occur on Mars every day. These events last, on average, about 30 minutes and range in size from meters to hundreds of meters in diameter. Designing low-cost missions that will improve our knowledge of dust devil formation and evolution, and their connection to atmospheric dynamics and the dust cycle, is fundamental to informing future crewed Mars lander missions about surface conditions. In this paper we present a mission for a constellation of low orbiting Mars cubesats, each carrying imagers with agile pointing capabilities. The goal is to maximize the number of dust devil follow-up observations through real-time, on-board scheduling. We study scenarios where cubesats are equipped with a 2.5 degree boresight angle camera that accommodates five slew positions (including nadir). We assume a concept of operations where the cubesats autonomously survey the surface of Mars and can autonomously detect dust devils from their surface imagery. When a dust devil is detected, the constellation is autonomously re-tasked through an on-board distributed scheduler to capture as many follow-on images of the event as possible, so as to study its evolution. The cubesat orbits are propagated assuming two-body dynamics and the ground tracks and camera field of view are computed assuming a spherical Mars. Realistic inter-agent communication link opportunities are computed and included in our optimization, which allow for real-time event detection information to be shared within the constellation. We compare against a powerful ``omniscient'' mission which has a priori knowledge of all dust devil activity to show the gap between predicted performance and the best possible outcome. In particular, we show that the communications are especially important for acquiring follow-up observations, and that a realistic distributed scheduling mechanism is sufficient to capture nearly all dust devil observations that are possible for a given orbit configuration.

Hook, Joshua Vander↗

NASA NTRS2021

The Case for a 50+ Year Radioisotope Power System

The Johns Hopkins University Applied Physics Laboratory (JHU/APL) is leading the NASA funded Interstellar Probe study to explore the “Very Local” interstellar medium. To perform this exploration the mission will be required to last at least 50 years in regions of space where solar power is no longer practical. Additionally, several new studies for the National Academies’ Planetary Science and Astrobiology Decadal Survey are planning missions lasting 20-35 years. The Decadal Survey is used to build consensus on priority of national science goals. These proposed missions are inconsistent with the NASA’s current Radioisotope Power Systems (RPS) life requirement of 14 years (flight). Paramount to these proposed long-duration missions are questions about the longevity of such a mission. Evidence exists that space-borne Radioisotope Power Systems can indeed last a long time. LES-9, Voyager I, and Voyager II are over 40 years old, LES-8, Pioneer 10, and Pioneer 11 lasted 28, 30, and 22 years, respectively, and New Horizons is still active 15 years after launch. This paper explores the need for RPS designs that are intended to last much longer than the current requirement of 14 years (17 years after fueling) and explores the historical record for actual vs design lifetimes to show the feasibility of building long lasting RPS. We also exercise a current RTG performance model of the General-Purpose Heat Source RTG using the JPL Lifetime Performance Prediction (LPP) tool to make top-level inferences about power output at end-of-mission, and discusses how reliability engineering and testing methods can be brought to bear to increase confidence in delivering sufficient power at end-of-mission.

Phan, Brian↗

NASA NTRS2022

Environmental Testing of Contamination Sensitive Instruments and Optics in Non-Cleanliness Controlled Facilities

The James Webb Space Telescope (JWST) Optical Telescope Element + Integrated Science Instrument Module (OTIS) went through environmental testing at the Goddard Space Flight Center. The vibration and acoustic tests occurred outside of cleanrooms. These areas are typically around ISO Class 8, far out of specifications for JWST. Through collaboration between the OTIS Mechanical and Contamination Engineering teams, a portable clean enclosure was designed, built, and verified to prevent contamination of the sensitive OTIS assembly. This manuscript describes the process of designing and building this enclosure, including materials selection and High Efficiency Particle Air (HEPA) filtration. This enclosure also provided environmental control with a portable air conditioning unit to control the relative humidity level enabling personnel to work within it. The manuscript emphasizes working in a systematic order to maintain cleanliness and integrity. “Clean as you go” during construction was a top priority to ensure that this critical Ground Support Equipment (GSE) was acceptable. The process of installing the walls and then sealing their internal and external surfaces with approved films was critical to maintaining OTIS integrity. This proved important because OTIS was in the enclosure for months longer than originally planned. This manuscript concludes by reviewing the process used to verify that the OTIS clean enclosure could achieve acceptable contamination level fallout accumulation for use during the vibration and acoustic testing and then verifying that the predicted performance was achieved after testing was complete.

Contamination Control, James Webb Space Telescope,↗

NASA NTRS2023

Fine particulate concentrations over East Asia derived from aerosols measured by the Advanced Himawari Imager using machine learning

Fine particulate matter with a diameter below 2.5 μm (PM 2.5 ) is deleterious to the cardiovascular and respiratory systems. It is often difficult to assess the effects of PM 2.5 on human health over regions with limited ground monitoring sites, especially in East Asia. As an alternative, we estimated near-surface PM 2.5 concentrations by analyzing Advanced Himawari Imager (AHI) Yonsei Aerosol Retrieval (YAER) products. This study incorporates daytime data for East Asia covering the Korean Peninsula, China, Japan, Southeast Asia, and southern Mongolia. We collocated AHI YAER product pixels with meteorological, land-cover, and other ancillary data for the period from March 2018 to February 2019. To estimate PM 2.5 concentrations over wide areas spanning many countries displaying various relationships between aerosol optical depth and PM 2.5 , monthly models were developed by considering both the spatial and temporal characteristics of ground-based PM 2.5 measurements. Random forest machine learning model estimated ground-level mass concentrations of PM 2.5 ; subsequent 10-fold cross validation (CV) yielded a CV R 2 value of 0.81 and a CV root mean squared error (RMSE) of 12.3 μg m -3 . We investigated the spatial pattern of PM 2.5 concentrations over multiple countries and seasonal variation in PM 2.5 concentrations. Diurnal variation of a severe PM 2.5 event in the Korean Peninsula was investigated as a case study. The model captured the extremely heterogeneous spatial distribution of PM 2.5 concentrations peaked around local noon. To measure the capability of the developed model to estimate PM 2.5 concentrations in areas with few in-situ data, its predictive performance was evaluated using a dataset independent of the training process with an R 2 of 0.60 and RMSE of 8.18 μg m −3 . This study demonstrates the potential for satellite-based PM 2.5 estimation for areas with insufficient measuring stations.

Pm2.5↗

NASA NTRS2021

Mars 2020 Perseverance Entry Descent and Landing Simulation Statistical Analysis and Operations

On February 18, 2021, the Perseverance rover and Ingenuity helicopter demonstra- tion landed at Jezero Crater. The Entry, Descent, and Landing (EDL) architecture, largely the same used to land Curiosity at Gale Crater on August 6, 2012, required high-fidelity flight dynamics simulation with two independent tools to verify per- formance. The process for creating the EDL simulation using the Dynamics Sim- ulator for Entry, Descent and Surface landing (DSENDS) tool will be discussed, along with its use for for independent verification of the EDL statistical analy- sis results and reference trajectory simulation. Analysis and usage details both in development and cruise, along with post-landing assessment of the prediction performance of the simulation, will also be discussed.

"O'Farrell, Clara"↗

NASA NTRS2021

The Effect of Transfer Line Length and Heat Rejection Temperature Distribution on the Thales Linear Pulse Tube (LPT) Cryocoolers

Four Thales LPT9310 and four Thales LPT9510 commercial off-the-shelf (COTS) cryocoolers were parametrically performance tested. The LPT9310 coolers had transfer lines of various lengths while the LPT9510 coolers all had the same transfer line geometry. The LPT9510 test results revealed unit-tounit thermodynamic performance variation, quantified the effect of compressor temperature on thermodynamic performance and quantified the heat flow distribution between the compressor and expander as a function of their temperature distribution. The LPT9310 test results revealed the optimal drive frequency as a function of transfer line length, quantified the effect of heat rejection temperature distribution on thermodynamic performance and enabled the development and verification of a thermodynamic performance prediction tool that accounted for cold tip temperature, heat lift, heat rejection temperature and transfer line length.

Rodriguez, J.I.↗

NASA NTRSDate not supplied

An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms

A surrogate artificial neural network/machine learning model was developed to predict the acoustic interaction for a fixed-pitch rotor in proximity to a downstream cylindrical airframe typical of small Unmanned Aerial System (sUAS) platforms. The model was trained to predict the acoustic waveform under representative hover conditions as a function of rotational speed, airframe proximity, and observer angle. Training data were acquired in an anechoic chamber on both isolated rotors and rotor-airframe configurations. Acoustic amplitude and phase of the revolution-averaged interaction were predicted, which required up to 25 harmonics to capture the impulse event caused by the blade’s approach and departure from the airframe. Prediction performance showed, on average, that the models could estimate the acoustic amplitude and phase over the relevant harmonics for unseen conditions with 86% and 75% accuracy, respectively, enabling a time domain reconstruction of the waveform for the range of geometric and flow parameters tested.

acoustics↗

NASA NTRSDate not supplied

An Artificial Neural Network Approach to Predict Rotor-Airframe Acoustic Waveforms

acoustics↗

NASA NTRSDate not supplied

Aero-Engines AI - A Machine-Learning App for Aircraft Engine Concepts Assessment

Effective deployment of trained machine-learning models could drive a high level of efficiency in aircraft engine conceptual design. Aero-Engines AI is a Windows app that has been created to deploy trained machine-learning models to assess aircraft engine concepts. It was created using tkinter, a GUI (graphical user interface) module that is built into the standard Python library. Employing tkinter greatly facilitates the sharing of machine-learning application as an executable file which can be run on Windows machines (without the need to have Python or any library installed). Current version of the app focuses on the performance prediction of conventional turbofans. The app gets user input for a turbofan design, preprocesses the input data, and deploys trained machine-learning models to predict turbofan thrust specific fuel consumption (TSFC), engine weight, core size, and turbomachinery stage-counts. The machine-learning predictive models were built by employing supervised deep-learning algorithm to study patterns in an existing open-source database of production and research turbofan engines. They were trained, cross-validated, and tested in Keras, an open-source neural networks API (application programming interface) written in Python, with TensorFlow (Google open-source artificial intelligence library) serving as the backend engine. The smooth deployment of these machine-learning models using the app shows that Aero-Engines AI is an easy-to-use and a time-saving tool for aircraft engine design-space exploration during the conceptual design stage.

machine learning↗

NASA NTRSDate not supplied

Validation of Universal Cryogenic Flow Boiling Correlations in Thermal Desktop for Liquid Methane and Liquid Nitrogen

Future in-space cryogenic architectures will depend on the ability to accurately model various stages of cryogenic propellant transfer and storage. Currently there is a need for more accurate, direct cryogenic data-anchored models for various boiling phenomena. This paper presents the implementation and validation of recently developed universal cryogenic flow boiling correlations for saturated flow boiling heat transfer coefficients (HTC) and critical heat flux (CHF) into the Thermal Desktop (SINDA/FLUINT) modeling software. The correlations are validated against steady state cryogenic flow boiling historical heated tube cases from liquid nitrogen and liquid methane experiments covering a wide range of inlet conditions, mass flux, and heat flux. Overall, Thermal Desktop with the new universal cryogenic flow boiling correlations demonstrates significant improvement in predictive performance for both wall temperature and CHF location compared to the Thermal Desktop model with built-in correlations when both are compared to the data.

Mariano Mercado↗

NASA NTRSDate not supplied

NavCube3-mini Lunar GNSS Receiver

This paper describes development and testing of NASA Goddard Space Flight Center’s new NavCube3-mini (NC3m) spaceborne, weak-signal GNSS receiver, which targets all Earth orbit regimes with special focus on lunar applications. NC3m derives from the ground-breaking Magnetospheric Multiscale (MMS) mission Navigator GPS receiver. The MMS-Navigator (launched 2015) holds a Guinness World Record for highest altitude GPS fix and is currently in a highly elliptic orbit with a 29 Earth radii apogee, nearly half lunar distance. NC3m has reduced size, weight, and power compared to the MMS-Navigator, making it suitable for smallsat applications, and adds multi-frequency and multi-GNSS capabilities, among other improvements. A NC3m engineering test unit was subjected to and successfully completed a comprehensive Technology Readiness Level 6 (system/subsystem model or prototype demonstration in a relevant environment) testing campaign in the second half of 2022. This involved high-fidelity simulations in LEO, GEO, and lunar regimes and full environmental testing, including vibration, thermal vacuum, and electromagnetic compatibility. An overview of the NC3m receiver, the test setup, and a sample of results is presented. The results include predicted performance at high-altitude and in the lunar regime.

NavCube3↗